Tessera

Sakana AI@sakanaai.bsky.social · 2w ago

Fugu-Ultra now works with Claude Code 🐡

Announcing the Claude Code-compatible interface for our new Fugu-Ultra v1.1! 🐡 sakana.ai/fugu-1-1-cla... Put a dynamically coordinated team of frontier models to work inside the coding workflow you already know.

Sakana AI@sakanaai.bsky.social · 2w ago

Our team just shipped Fugu-Ultra v1.1! 🐡 By dynamically orchestrating the latest frontier models, we pushed performance up by 7.9 points. We are now beating Fable 5 in complex coding and reasoning tasks without even having Fable 5 in our agent pool. Collective intelligence is the future.

Announcing Fugu-Ultra v1.1 🐡 We’ve been thrilled by the reception to the Fugu model family. Thanks to everyone who tried it, shared feedback, and trusted Fugu with real work. Today, we’re releasing Fugu-Ultra v1.1 → sakana.ai/fugu Upgraded to incorporate the latest frontier models.

Sakana AI @sakanaai.bsky.social · 2w ago

Announcing Fugu-Ultra v1.1 🐡 We’ve been thrilled by the reception to the Fugu model family. Thanks to everyone who tried it, shared feedback, and trusted Fugu with real work. Today, we’re releasing Fugu-Ultra v1.1 → sakana.ai/fugu Upgraded to incorporate the latest frontier models.

Schmidhuber being Schmidhuber 🔥

Schmidhuber: I support open-source models distilling what commercial companies distilled for free from the entire internet. I published distillation for free in 1991 in Europe - this was copied in the US and in China (https://x.com/SchmidhuberAI/status/1608870559609421831)

Quoted:
Director Michael Kratsios (US government worker)

We have information that Moonshot AI distilled Anthropic’s Fable for the development of its K3 model.

To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection. Moonshot AI has also acquired GB300-equipped servers and has accessed GB300s in Thailand, likely to train its AI models.

The United States strongly supports the free and fair development of AI, including a thriving competitive ecosystem that spans frontier models, specialized systems, open-source frameworks, and open-weight models. Legitimate AI distillation used to create smaller, more efficient models plays a vital role in this open innovation ecosystem. However, large-scale, covert industrial distillation aimed at stealing proprietary U.S. technology and undermining American research is unacceptable.

Sakana AI@sakanaai.bsky.social · 2w ago

Incredibly proud of the Sakana AI team. We have developed an orchestration model right here out of Japan that achieves state-of-the-art performance on real-world cybersecurity benchmarks! 🎌 sakana.ai/fugu-cyber-r...

Introducing Fugu-Cyber: an update to our Fugu orchestration model. It achieves state-of-the-art performance on real-world security benchmarks, matching cyber-focused frontier models like GPT-5.5-Cyber and Mythos Preview. Release Blog: sakana.ai/fugu-cyber-r... 🐡

hardmaru @hardmaru.bsky.social · 3w ago

Language models and coding agents are great, but there is more to life, and more to AI, than just LLM agents.

hardmaru @hardmaru.bsky.social · 3w ago

How do physical systems achieve collective intelligence and self-repair without a central brain? A new paper published in Nature Communications from Sakana AI, IT University of Copenhagen, Autodesk, presents a beautiful realization of biologically inspired robotics: Smart Cellular Bricks. Thread 🧵

Sakana AI@sakanaai.bsky.social · 3w ago

We are pleased to share our latest research, now published in Nature Communications: “Smart Cellular Bricks: Physical Modules That Recognize Their Own Shape and Repair Themselves.” Blog: sakana.ai/smart-cellul... Paper: www.nature.com/articles/s41... Thread 🧵

hardmaru @hardmaru.bsky.social · 4w ago

One of my first journeys in neural networks started over a decade ago with implementing CPPN-NEAT! Back then, I built a clone of ‘Picbreeder’ not only to study the mechanics of neural nets, but to explore the human creativity process itself, and generate some cool abstract art.

neurogram

ōtoro.net

otoro.net

Sakana AI@sakanaai.bsky.social · 4w ago

The AI Picbreeder Experiment: Can AI agents be creative when nobody tells them what to create? Blog: pub.sakana.ai/picbreeder-vlm Paper: arxiv.org/abs/2605.23908 In our #GECCO2026 paper, we revisit Picbreeder, a website where people collaboratively evolved images without any predefined objective.

Takashi Ishida @tksiia.bsky.social · last mo.

Fugu-Ultra is now available on Vercel AI Gateway vercel.com/changelog/sa... ✨

Excited to share CoffeeBench!!☕️☕️☕️ We evaluate LLM agents in a 90-day B2B coffee supply-chain economy spanning farmers, roasters, and retailers, where autonomous firms negotiate, manage inventory, set prices, handle invoices, and manage cash flow. arxiv.org/abs/2606.16613 github.com/sakanaai/cof...

hardmaru @hardmaru.bsky.social · last mo.

Fugu-Ultra is now live on OpenRouter! ⚡ We share a core vision with the OpenRouter team: the future of AI isn’t a single monolithic model, but the collective intelligence of the world’s best models working together. Try it: openrouter.ai/sakana/fugu-... 🐡

Excited to partner with OpenRouter ⚡ Products like OpenRouter Fusion and Sakana Fugu have sparked a serious conversation about dependency and resilience in AI. I believe this is just the start of a massive architectural shift to come in AI development.

Sakana AI@sakanaai.bsky.social · last mo.

Fugu-Ultra is now live on OpenRouter! ⚡ We share a core vision with the OpenRouter team: the future of AI isn’t a single monolithic model, but the collective intelligence of the world’s best models working together. Try it: openrouter.ai/sakana/fugu-... 🐡

hardmaru @hardmaru.bsky.social · last mo.

Human intelligence is fundamentally a collective intelligence. We solve complex problems by participating in a vast cultural network that builds upon ideas across generations. I believe the strongest AI systems will become a collective intelligence, too.

Sakana AI@sakanaai.bsky.social · last mo.

Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API. Our ‘Fugu Ultra’ model matches the performance of Fable and Mythos, delivering frontier capability without the risk of export controls. Try it: sakana.ai/fugu 🐡

Sakana Fugu: One Model to Command Them All Frontier-level performance without single-vendor dependency. Fugu dynamically orchestrates the world's best models to tackle complex, multi-step tasks. Plug collective intelligence directly into your workflows today with a single API. sakana.ai/fugu/

Sakana Fugu — Multi-agent System as A Model

One model to command them all

sakana.ai

How does it work? Sakana Fugu is itself an LLM, trained to call various LLMs in an agent pool, including instances of itself recursively. Fugu dynamically orchestrates the world's best models to tackle complex, multi-step tasks. Here, Fugu is a multi-agent system that behaves like a single model.

Fugu stands shoulder-to-shoulder with leading models like Fable and Mythos across the industry's most rigorous engineering, scientific, and reasoning benchmarks. Read the full blog: sakana.ai/fugu-release Beyond Bigger Models: Why are Orchestration Models the Next Frontier (Thread Below)

Introducing Sakana Fugu: A full multi-agent orchestration system accessible via a single model API. Our ‘Fugu Ultra’ model matches the performance of Fable and Mythos, delivering frontier capability without the risk of export controls. Try it: sakana.ai/fugu 🐡

Reproducing all of Jürgen Schmidhuber’s papers (1990-2025) using an AI coding assistant. Cool project by Yaroslav! It even reproduced the “World Models” paper by me and Schmidhuber (2018) using a toy environment, with a full VAE + RNN world model implementation. Project: github.com/cybertronai/...

hardmaru@hardmaru.bsky.social · 3mo ago

How do we make LLMs faster and lighter? Don’t force the GPU to adapt to sparsity. Reshape the sparsity to fit the GPU! Our latest work with NVIDIA introduces new CUDA kernels & data formats for faster inference and training of sparse transformer language models: Blog: pub.sakana.ai/sparser-fast...

Excited to share Sakana AI’s new #ICML2026 paper in collaboration with NVIDIA: "Sparser, Faster, Lighter Transformer Language Models" arxiv.org/abs/2603.23198 This work introduces new open-source GPU kernels and data formats for faster inference and training of sparse transformer LLMs: 🧵 Thread 👇

Excited to share Sakana AI’s new #ICML2026 paper in collaboration with NVIDIA: "Sparser, Faster, Lighter Transformer Language Models" arxiv.org/abs/2603.23198 This work introduces new open-source GPU kernels and data formats for faster inference and training of sparse transformer LLMs: 🧵 Thread 👇

If GitHub were built in: Japan 🇯🇵 China 🇨🇳 North Korea 🇰🇵 The EU 🇪🇺

Source: https://twitter.com/almmaasoglu/status/2050603144686473246

Source: https://twitter.com/jonasfroeller/status/2050288312213004578

https://twitter.com/hardmaru/status/2050783184745545850

https://twitter.com/TheEthanDing/status/2050575592886812993

Sakana AI@sakanaai.bsky.social · 3mo ago

For the past few years, humans have been doing “prompt engineering” to coax the best performance out of different LLMs. In this work, we explored what happens if we train an AI to do that job instead. Link to our #ICLR2026 paper: arxiv.org/abs/2512.04388 Thread:

Introducing our new work: “Learning to Orchestrate Agents in Natural Language with the Conductor” accepted at #ICLR2026 arxiv.org/abs/2512.04388 What if we trained an AI not to solve problems directly, but to act as a manager that delegates tasks to a diverse team of other AIs? Thread:

Introducing our new work: “Learning to Orchestrate Agents in Natural Language with the Conductor” accepted at #ICLR2026 arxiv.org/abs/2512.04388 What if we trained an AI not to solve problems directly, but to act as a manager that delegates tasks to a diverse team of other AIs? Thread:

日経クロステックの連載記事「R&Dを根底から変革、普及始まる『AI科学者』」にて、Sakana AIのResearch Scientist、Robert Langeへの取材記事が掲載されました。当社のAIサイエンティストについて、テーマ探索から論文査読まで研究の全工程を自動的に遂行する仕組みと、その現状の到達点・限界について解説されています。記事でも触れていただいているとおり、AIサイエンティストに関する論文は2026年3月に学術誌Natureに掲載されました。基盤となるAIモデルの性能向上に伴って生成される論文の質が改善されうることを実験的に示せた点は、本研究の重要な成果の一つです。

Sakana AIとGoogleのAI科学者、自律性に差　研究の種を生むのは人間

CraifはAI科学者で研究の時間を大幅に短縮し、NanoFrontierはAI科学者のプロセスを前提とした事業を立ち上げた。大手製薬などもAI科学者ツールの導入を始めている。AI科学者の全体像を整理する。

xtech.nikkei.com

Sakana AI@sakanaai.bsky.social · 3mo ago

Scaling up massive LLMs continues to yield incredible results. But to truly unlock their full potential, the next frontier is test-time compute and dynamic orchestration.

What if instead of building one giant AI, we evolved a coordinator to orchestrate a diverse team of specialized AIs? 🐟 Excited to share our new #ICLR2026 paper: “TRINITY: An Evolved LLM Coordinator”! Paper arxiv.org/abs/2512.04695 OpenReview openreview.net/forum?id=5Ha... Fugu sakana.ai/fugu-beta